Improving Exploratory Search Experience through Hierarchical Knowledge Graphs

Sarrafzadeh, Bahareh; Lank, Edward

doi:10.1145/3077136.3080829

Cited by 20 publications

(16 citation statements)

References 28 publications

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“…Exploratory search requires the latest human-machine interfaces to increase speed of user resource analysis and decision making on further movement through information resources. [28,29] suggest the use of concept maps for exploratory search. Sarrafzadeh [29] uses hierarchical and nonhierarchical concept graphs to present search results.…”

Section: Knowledge Assessmentmentioning

confidence: 99%

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Concept Maps, Their Application Types and Methods in Information and Learning Systems

Tytenko

2021

KPI SN

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Background. The hypermedia environment, which has received a powerful technical infrastructure thanks to the WWW, has led to the study and emergence of new forms and tools of information and educational content presentation. Various methods and means of visualization of educational information increase clarity and facilitate the process of new knowledge perception. Such tools include a wide range of concept maps that have become widespread in many areas related to information technology and education. The challenge here is to find comprehensive solutions that will reduce computing and labor costs for the multifunctional use of concept maps in information and learning systems. Objective. The work is focused on the review of concept maps, research of preconditions for their origin, analysis of their types and purposes of application in the educational process and learning systems. The main task is to analyze the requirements for interactive concept maps in ontology-oriented information systems to support lifelong learning. Methods. The use of concept maps in educational systems is based on knowledge modeling, graph theory, ontological modeling of educational content and methods of adaptive e-learning systems. The paper reviews and analyzes the application of concept maps and requirements for them within the information and learning systems. Results. Concept maps have significant foundation in cognitive and educational psychology, computational linguistics, knowledge engineering and have widespread application in computer supported learning. Concept maps are used as a means of meaningful learning when constructed by students, used to assess knowledge, as well as a means of navigating information resources. Concept maps in educational systems are used to present knowledge to users and serve as interfaces in the process of exploratory search and review of study areas. Information systems provide enrichment of concept maps by means of interactivity, which allows diversifying and expanding its use. Conclusions. The key requirements for interactive concept maps in information and learning systems are formed, including automation of interactive concept map construction, availability of wide navigation capabilities together with cognitive load control, implementation of interdisciplinary links, media annotation of map elements, complex application of graph interfaces for different parts of the system and adaptation to mobile devices.

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Section: Knowledge Assessmentmentioning

confidence: 99%

“…[28,29] suggest the use of concept maps for exploratory search. Sarrafzadeh [29] uses hierarchical and nonhierarchical concept graphs to present search results. Falke [28] offers automated text annotation in the form of concept maps and their use in interfaces of the exploratory search system.…”

Section: Knowledge Assessmentmentioning

confidence: 99%

Concept Maps, Their Application Types and Methods in Information and Learning Systems

Tytenko

2021

KPI SN

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“…Graph navigation systems. User interfaces for query formulation [9,10,15,17,34] either (i) assume the user can navigate through the entire graph structure (often ranking suggestions in decreasing frequency order [10]), but do not restrict the potentially large number of expansions [9,15,30], or (ii) rely on heuristic approaches based on query logs [17]. Similarly, faceted search allows smart filtering of large result sets along different attributes [13].…”

Section: Related Workmentioning

confidence: 99%

Graph-Query Suggestions for Knowledge Graph Exploration

Lissandrini

Mottin

Palpanas

et al. 2020

Proceedings of the Web Conference 2020

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We consider the task of exploratory search through graph queries on knowledge graphs. We propose to assist the user by expanding the query with intuitive suggestions to provide a more informative (full) query that can retrieve more detailed and relevant answers. To achieve this result, we propose a model that can bridge graph search paradigms with well-established techniques for informationretrieval. Our approach does not require any additional knowledge from the user and builds on principled language modelling approaches. We empirically show the effectiveness and efficiency of our approach on a large knowledge graph and how our suggestions are able to help build more complete and informative queries.

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“…The important feature of an ES system is itscapabilityy to demonstrate data in a way that favors emergence arrangements and provides new insights. Various types of visualizations can be employed on search outcomes or facets [24].…”

Section: Exploratory Visual Searchmentioning

confidence: 99%

Towards Improving Exploratory Faceted Search Results

2020

IJATCSE

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Finding information on the web, containing billions of documents, is becoming a serious issue. Search engines (SE) help users find handy information such as videos, text or pictures. For open-ended results, users need to perform queries in order to find enough information about their topic of interest. This can be difficult when huge numbers of relevant and irrelevant results are returned from the queries causing information overload. Certain SEs incorporating visualization allow easy understanding of the documents and often reduce the Information overload issues. Sorting of more relevant results from the less relevant ones is difficult since the former is insufficient. This is obvious when the Web grows and the information therein increases to become larger data repositories. The query and response (lookup) processes are often used by most current SEs. Exploratory Search (ES) can provide open ended search. Therefore, the overall search can be improved by applying the Faceted search (FS), which is one of the features of ES. Studies have mentioned that the overloaded data can be reduced when traditional SEs are replaced with the ES, through their features. The prototype design we are working on is based on the idea of ES engine that can be used to visualize the information when exploring the Web. This concept is aimed at supporting more active means of finding information through coordinated visualizations and reducing large amount of search efforts required per query. The prototype system was evaluated for performance and compared with CloudMining SE. The results show that our prototype gives average improvement of 20% relevant results when compared with CloudMining SE.

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Improving Exploratory Search Experience through Hierarchical Knowledge Graphs

Cited by 20 publications

References 28 publications

Concept Maps, Their Application Types and Methods in Information and Learning Systems

Concept Maps, Their Application Types and Methods in Information and Learning Systems

Graph-Query Suggestions for Knowledge Graph Exploration

Towards Improving Exploratory Faceted Search Results

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